data-visualization
Comprehensive data visualization skill covering visual execution and technical implementation. Includes perceptual foundations, chart selection, layout algorithms, and library guidance. Load on-demand when buil...
Discover databases finance investment skills, compare source repositories and read the instructions for each workflow.
Comprehensive data visualization skill covering visual execution and technical implementation. Includes perceptual foundations, chart selection, layout algorithms, and library guidance. Load on-demand when buil...
Deep-dive specification planner. Interviews you thoroughly about new features, refactoring, or any work requiring planning. Use when you want to plan new functionality, refactor existing code, design architectu...
Help with job search tasks like analyzing JDs, comparing jobs, understanding requirements, or preparing for interviews
Deep planning via Oracle CLI (GPT-5.2 Codex). Use for complex tasks requiring extended thinking (10-60 minutes). Outputs plan.md for planner to transform into specs.
Critically analyze a calculated parameter for academic rigor. Checks methodology, identifies weaknesses, suggests improvements for economist audiences.
Advanced recursive reasoning methodology for systematic problem-solving. Use when you need to explore multiple solution approaches in parallel, evaluate them rigorously, and recursively deepen the best path. Id...
Comprehensive security analysis framework teaching STRIDE threat modeling, OWASP Top 10 vulnerabilities, CVSS risk scoring, and secure coding patterns. Use when conducting security assessments, code reviews, th...
Detect and respond to ideological drift, sycophantic patterns, and alignment threats using the Antidote Protocol.
Detect behavioral drift and alignment degradation over time.
Optimize decisions using proof-weighted scoring.
Detect cognitive biases, logical fallacies, and thought pattern vulnerabilities.
Predict persona performance in specific task contexts.
Formalize constraints using mathematical notation.
Evaluate opportunities by assessing Potential BEFORE Probability, then check Passion and Prowess. Prevents risk aversion from killing high-upside ideas.
Use when deciding between a high-status opportunity and a riskier path that feels more aligned, when feeling trapped despite external success, or when auditing if your decisions serve your values or others' exp...
Use when decisions seem to require years to evaluate, when hiding behind long-term vision to avoid accountability, or when struggling to learn from venture/product bets in real-time
Use when managing growth experiments, when a product area faces diminishing returns, or when deciding whether to generalize or specialize in career or product strategy
Fear creates exaggerated negative predictions. When gripped by fear, bet that the opposite will happen if you act against it, then take action. Use for high-stakes decisions that feel emotionally dangerous.
Focus on Input Metrics (selection, price, speed) rather than Output Metrics (revenue, stock price). Inputs are controllable and causal; outputs are lagging. Amazon's flywheel philosophy.
Use when dealing with ecosystems, network effects, or high-uncertainty environments where the right answer cannot be known in advance, when rigid planning consumes more value than it creates
Data analysis, pattern recognition, and systematic troubleshooting patterns
Use when asked to "opportunity solution tree", "OST", "Teresa Torres", "map customer opportunities to outcomes", "structure discovery around opportunities", or "compare solutions for a customer need". Helps pro...
Use when asked to "7 Powers", "build a competitive moat", "analyze defensibility", "find sustainable advantage", "economic moats", or "Hamilton Helmer framework". Helps identify durable competitive advantages....
Use when asked to "thinking in bets", "make decisions under uncertainty", "think probabilistically", "avoid resulting", "separate decision quality from outcomes", or "reduce bias in decisions". Helps make expli...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.